# How to integrate Procfu MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Procfu MCP with OpenAI Agents SDK",
  "toolkit": "Procfu",
  "toolkit_slug": "procfu",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/procfu/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/procfu/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-06T08:24:38.041Z"
}
```

## Introduction

This guide walks you through connecting Procfu to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Procfu agent that can find new entries in updated google sheet, delete a specific file from google drive, generate random test users for qa through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Procfu account through Composio's Procfu MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Procfu with

- [Claude Agent SDK](https://composio.dev/toolkits/procfu/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/procfu/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/procfu/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/procfu/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/procfu/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/procfu/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/procfu/framework/cli)
- [Google ADK](https://composio.dev/toolkits/procfu/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/procfu/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/procfu/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/procfu/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/procfu/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/procfu/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Procfu
- Configure an AI agent that can use Procfu as a tool
- Run a live chat session where you can ask the agent to perform Procfu operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## What is the Procfu MCP server, and what's possible with it?

The Procfu MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Procfu account. It provides structured and secure access to advanced Podio automations, letting your agent compare arrays, generate test data, interact with Google Drive and Sheets, and even harness OpenAI for creative tasks—all on your behalf.
- Automated data comparison and manipulation: Have your agent find differences, additions, deletions, or intersections between two JSON arrays to quickly analyze data changes or synchronize lists.
- Google Drive file management: Direct your agent to delete files or folders from your Google Drive, streamlining cleanup and organization without manual effort.
- Dynamic test data and placeholder generation: Instantly generate dummy emails, numbers, images, or addresses for testing, prototyping, or populating demo environments.
- Retrieve Google Sheets data: Ask your agent to pull contents from a specific Google Sheet as an array, making it easy to process, analyze, or migrate spreadsheet data.
- Conversational AI and image generation: Let your agent query OpenAI GPT for answers or generate new images from text prompts, extending automation into creative and cognitive tasks.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PROCFU_ARRAY_DIFF_DEL` | Array Difference Deletions | Tool to return items removed when comparing two JSON arrays. Use when you have two arrays and need to know which elements were deleted. |
| `PROCFU_ARRAY_DIFF_NEW` | Array Diff New | Tool to return items added in the second JSON array. Use when you need to identify new elements between two list versions. Example: Compare [1,3,4] vs [1,3,6] to get [6]. |
| `PROCFU_ARRAY_DIFF_SAME` | Array Diff Same | Tool to get items present in both JSON arrays. Computes the intersection locally to avoid external API dependency. Rules: - Two items are considered equal if their JSON representations match (with sorted keys for objects). - The result contains unique items present in both arrays, preserving the order they appear in json_array_b. |
| `PROCFU_ARRAY_SORT` | Array Sort | Tool to sort a JSON array of values. Use when you need to order elements ascending or descending. |
| `PROCFU_DELETE_GOOGLE_DRIVE` | Delete Google Drive | Tool to delete a Google Drive file or folder. Use after obtaining a valid Google Drive ID. |
| `PROCFU_DUMMY_DATA` | Generate dummy data | Tool to generate dummy data. Use when you need random emails, text, numbers, dates, people, addresses, or images for testing or placeholder data. |
| `PROCFU_GOOGLE_DRIVE_DELETE` | Google Drive Delete | Tool to delete a Google Drive file or folder. Use after obtaining a valid Google Drive ID. |
| `PROCFU_OPEN_AI_GPT` | Ask question to OpenAI GPT | Tool to ask a question to OpenAI GPT. Use when you need a conversational answer from GPT. |
| `PROCFU_OPEN_AI_IMAGE` | Generate Image with OpenAI | Tool to generate an image via OpenAI API. Use when you need programmatic image creation from a text prompt. |
| `PROCFU_SHEETS_GET` | Get Google Sheet contents as array | Tool to get sheet contents as array. Use when you need to retrieve Google Sheet data as an associative array. |
| `PROCFU_SHEETS_GET_METADATA` | Get Google Sheets Metadata | Tool to retrieve metadata of a Google Sheets spreadsheet, including sheet names, IDs, and properties. Use when you need sheet-level details for a given spreadsheet ID. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Procfu MCP server is an implementation of the Model Context Protocol that connects your AI agent to Procfu. It provides structured and secure access so your agent can perform Procfu operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Procfu project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Procfu.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only procfu.
- The router checks the user's Procfu connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Procfu.
- This approach keeps things lightweight and lets the agent request Procfu tools only when needed during the conversation.
```python
# Create a Procfu Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["procfu"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Procfu
const session = await composio.create(userId as string, {
  toolkits: ['procfu'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Procfu. "
        "Help users perform Procfu operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Procfu. Help users perform Procfu operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["procfu"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Procfu. "
        "Help users perform Procfu operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['procfu'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Procfu. Help users perform Procfu operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Procfu MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Procfu.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Procfu MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/procfu/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/procfu/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/procfu/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/procfu/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/procfu/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/procfu/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/procfu/framework/cli)
- [Google ADK](https://composio.dev/toolkits/procfu/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/procfu/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/procfu/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/procfu/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/procfu/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/procfu/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Procfu MCP?

With a standalone Procfu MCP server, the agents and LLMs can only access a fixed set of Procfu tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Procfu and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Procfu tools.

### Can I manage the permissions and scopes for Procfu while using Tool Router?

Yes, absolutely. You can configure which Procfu scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Procfu data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)